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State-of-the-art study of Python libraries for orbit propagation, comparison of poliastro & Tudatpy with CelestLab & GMAT

Authors: Muller, Arnaud;

State-of-the-art study of Python libraries for orbit propagation, comparison of poliastro & Tudatpy with CelestLab & GMAT

Abstract

As part of an effort to streamline the space mission design workflow of the CREME satellite mission into a single-language process, this study provides a list of open-source Python libraries capable of orbit propagation and a comparison of their feature set. Two libraries selected as prime candidates are compared across three different force models with trusted reference tools based on their numerical results, computation time and ease of use. Both are found to be suitable options for different use cases, with faster and more modular computations being their strongest advantages, whereas the reference tools remain particularly compelling for their accessibility when used independently.

{"references": ["ONERA, \"Space weather: a nanosatellite to measure radiation,\""]}

Keywords

python, astrodynamics, orbit

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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